Remote Sensing (Oct 2022)

Real-Time Source Modeling of the 2022 Mw 6.6 Menyuan, China Earthquake with High-Rate GNSS Observations

  • Zhicai Li,
  • Jianfei Zang,
  • Shijie Fan,
  • Yangmao Wen,
  • Caijun Xu,
  • Fei Yang,
  • Xiuying Peng,
  • Lijiang Zhao,
  • Xing Zhou

DOI
https://doi.org/10.3390/rs14215378
Journal volume & issue
Vol. 14, no. 21
p. 5378

Abstract

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On 7 January 2022, a Mw 6.6 earthquake struck Menyuan County in the Qinghai province of China and the earthquake caused severe damage to infrastructures. In this study, the performance of the high-rate global navigation satellite system (GNSS) on real-time source modeling of the 2022 Mw 6.6 Menyuan earthquake was validated. We conducted the warning magnitude calculation, centroid moment tensor (CMT) inversion, and static fault slip distribution inversion using displacements collected from 14 1-Hz GNSS stations. Our results indicate that the warning magnitude derived from the peak ground displacement (PGD) first exceeds Mw 6.0 approximately 9 s after the earthquake and tends to be stable after about 45 s. The derived finally stable magnitude is Mw 6.5, which is near the USGS magnitude of Mw 6.6. Based on the inverted CMT and static fault slip distribution results, it can be determined that the 2022 Menyuan earthquake is a left-lateral strike-slip event after about 20 s of the earthquake. Although the fault slips, inverted with the 30-s smoothed coseismic offsets, are unstable after about 40 s, all the inverted slip models after that time present the obvious surface rupture and the most fault motions are concentrated between the depth of 0 km and 8 km. Compared with the results inverted with the 30-s smoothed coseismic offsets, the CMT and fault slips inverted with the 70-s smoothed coseismic offsets are more stable. The results obtained in this study indicate that the high-rate GNSS has the potential to be used for real-time source modeling for earthquakes with a magnitude less than 7; the stability of the inverted CMT and fault slips can be improved by using the coseismic offsets averaged by a relatively long-time sliding window.

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